The tool can guide personalized screening intervals, identifying low-risk individuals for longer gaps and high-risk individuals for enhanced surveillance such as MRI.

Equity is highlighted, with evidence that Clairity Breast performs well across diverse racial and ethnic groups, addressing gaps in traditional models.

This update reflects a broader movement toward precision prevention and dynamic, risk-informed screening with implications for health systems, payers, and patient care.

Ongoing research envisions monitoring chemoprevention efficacy by tracking changes in the AI risk score over time.

Future refinements may include subtype-specific risk prediction and preventive approaches such as vaccines, though these require further research and trials.

Clairity announces that NCCN guidelines now incorporate an FDA-authorized AI-based mammogram analysis tool to assess five-year breast cancer risk, signaling a shift toward precision prevention in screening and prevention.

The risk assessment is to be periodically reassessed and expanded to start at age 35, enabling earlier intervention for those at elevated risk.

Clairity emphasizes that its FDA-cleared imaging-based AI model can provide actionable five-year risk at the point of care, supporting more precise, individualized care without replacing the radiologist’s read.

Leadership from Clairity and other medical experts outline the potential impact on clinical practice, payer policies, and health-system strategies.

Data supporting equitable performance come from a study across MIT, Mass General, and international sites, totaling over 62,000 patients and 128,000 mammograms.

The technology is positioned as a second, independent data point that enriches decision-making while preserving the radiologist’s standard read.

The approach shifts from detection to prediction, enabling personalized prevention and dynamic reassessment as risk evolves.